🎓 ElevatePath AI

AI-powered career guidance system designed to help students and professionals choose the right career path based on their skills, interests, and goals.

🚀 Features

• 🎯 Career Recommendation Agent: Suggests suitable roles
• 📊 Skill Gap Analysis: Identifies missing skills
• 🛣️ 6-Month Learning Roadmap: Creates structured learning plans
• 🤖 AI Impact Analysis: Explains future trends and how to stay resilient
• 📂 Dataset-driven Insights: Enhanced recommendations using local JSON profiles
• 🧠 Multi-Agent Architecture: Collaborative workflows powered by Google Gemini
• 🌐 Interactive UI: Clean and intuitive Streamlit interface

🏗️ Architecture

This project follows a multi-agent system design to provide deep, contextualized guidance:

1. Career Agent → Analyzes background and suggests matching roles from the dataset.
2. Skill Gap Agent → Contrasts current capabilities with the requirements of proposed roles.
3. Roadmap Agent → Formulates structured learning milestones (Months 1-6).
4. AI Impact Agent → Analyzes future trends and market-resilience strategies.

All agents are powered by the Google Gemini API (gemini-2.5-flash) and leverage local dataset templates.

📁 Project Structure

ElevatePath-AI/
├── app.py                  # Main Streamlit application entry point
├── agents/                 # Multi-agent core logic
│   ├── career_agent.py      # Role suggestion agent
│   ├── skill_gap_agent.py   # Skill deficiency identifier
│   ├── roadmap_agent.py     # Milestone planning agent
│   └── ai_impact_agent.py   # Future-proofing and AI analysis agent
├── utils/                  # Shared utilities
│   ├── gemini_client.py     # Google GenAI API communication client
│   └── load_careers.py      # Dataset loader utility
├── data/                   # Structured career profiles
│   └── careers.json         # Base dataset with requirements and outlooks
├── requirements.txt        # Python package dependencies
└── README.md               # Project documentation

🛠️ Setup & Execution

1. Prerequisites

Ensure you have Python 3.10+ installed.

2. Install Dependencies

Install the required libraries:

pip install -r requirements.txt

3. Run the Application

Launch the Streamlit app:

streamlit run app.py

4. Provide API Credentials

Enter your Google Gemini API key in the UI to authenticate the agents.

Built With

• python